Deo S.

In this clip, Dinesh Nithyanandam gives a brief overview of the OSI Model and its relevance to traffic routing during Canary deployments. #slo #observability #reliability #sre #devops #engineering

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Till now after spending more than 20 hours of effort for the remediation of the BSOD issue for our client using different ways like root volume change using snapshot and ec2 rescue for AWS Cloud EC2 WINDOWS VM. i thought of writing up this small blog from my experience. Importance of Security, High Availability, and Automation in the Age of Cloud Recent events with a leading cybersecurity platform highlight the critical intersection of security, high availability, and automation in today's technology landscape. While specific details of the incident are not discussed here let's explore these key takeaways for leaders: Prioritizing Security: * Endpoint Detection and Response (EDR): Solutions like CrowdStrike's Falcon platform exemplify the importance of EDR capabilities. They go beyond mere threat detection by actively stopping them in their tracks. * Continuous Monitoring and Testing: Security requires constant vigilance. Vulnerability assessments and rigorous testing of updates before deployment are crucial. Ensuring High Availability: * Redundancy is Key: Implementing redundant systems allows for quick rollbacks in case of unforeseen issues. This minimizes downtime and protects critical business operations. * Disaster Recovery (DR) Plans: Having a tested DR plan ensures swift and coordinated responses to outages. Embracing Automation: * Automated Rollback Mechanisms: Streamlining rollbacks through automation minimizes disruptions and simplifies recovery efforts. * Automated Patching Practices: Automated patching can improve efficiency, but it should be well-tested and have proper safeguards in place. Lessons Learned: * Security Updates Can Introduce Risk: Even security updates can have unintended consequences. Thorough testing is essential to avoid disrupting critical systems. * Communication is Paramount: Clear and timely communication with stakeholders during outages builds trust and fosters transparency. * Learn and Adapt: Debriefing after incidents helps identify vulnerabilities and implement preventive measures to avoid similar situations in the future. Investing in the Future: * Security Code Analysis (SCA) Tools: SCA tools can identify potential vulnerabilities in code before they become security risks. * Phased Patch Rollouts: Implementing patches in phases allows for early detection and mitigation of any unforeseen issues. Conclusion: Leaders must prioritize security, high availability, and automation to build resilient systems. By continuously learning and adapting, we can ensure the smooth operation of critical infrastructure and maintain customer trust. #automation #cybersecurity #DR #Resiliency #security #Cloud

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#Docker is powerful & complex🤯Even the seasoned user might miss out on its nuanced capabilities! Tomorrow, at Cloud Native Pune, Rashi Chaubal will be sharing the Docker, Inc playbook to reveal the essential tips, tricks & best practices🚢 RSVP to join👇 https://lnkd.in/du6y4yb6

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Yahoo’s Kubernetes Journey from on-Prem to Multi-Cloud   🎯 Key Innovations:     - Migrated from on-prem infrastructure to a multi-cloud ecosystem with GCP and AWS.     - Developed ‘Omega’ interface simplifying app deployment to Kubernetes clusters.     - Introduced ‘Cadence’ tool for seamless cluster creation across multiple clouds.    💡 Notable Features:     - **Omega YAML**: A simplified deployment template ensuring quick app setups.     - **Cadence Tool**: A Golang-based tool for managing EKS and GKE workloads without deep cloud provider knowledge.     - **Node Manager Operator**: Automates Kubernetes version upgrades while maintaining workloads.    🛠️ Perfect for:     - Cloud Engineers     - Kubernetes Administrators     - DevOps Teams     - Platform Engineers     - Organizations transitioning to multi-cloud environments    ⚡️ Impact:     - Enhanced deployment efficiency by streamlining application setups.     - Achieved significant cost reduction for operations in cloud environments.     - Facilitated rapid responses to infrastructure changes and reduced upgrade times from months to weeks.    🔍 Preview of the Talk:     Nandhakumar Venkatachalam and Payal Patel from Yahoo discuss the company's transition from a traditional on-prem environment to a cutting-edge multi-cloud strategy using Kubernetes. They delve into the challenges faced, such as networking and security, while showcasing breakthrough tools like Omega and Cadence. The talk emphasizes how these innovations enhance user experiences and streamline operations. Participants will gain valuable insights into effective cloud strategies and operational efficiencies in Kubernetes environments. Watch the full session: https://lnkd.in/gcZS--rY

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Running Kubernetes in production I have been running Kubernetes in production for almost 6-7 years and if you ask me today I have to choose between managed or self-hosted control plane. I will go for managed. The reason is that I will save a huge cost that I may have to spend on engineering while taking care of the clusters and utilizing the engineering effort somewhere. Obviously, running your self-hosted control plane gives you control and a tremendous opportunity to learn but the cost of managing outweighs the learning. Also, team size and organization alignment do contribute to this decision. Here is a small writeup on why you can choose it. Will also write why you should choose it. Do follow and share so that it can reach the right people. https://lnkd.in/g-W6AV6r #kubernetes #production #sre #devops #linux

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DM me #DevSecOps folks !! ( #immediate ) Strong fundamentals with at least 2.5 -4 years implementation exp : Gradle, GIT, MS Azure (ARM templates, AKS, GitHub Adv Security( #ghas), Application gateway, #Azure AD)Frameworks: #Kubernetes, Gradle, #GitHubActions , CICD set up azure deployment, terraform script understanding .

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Organizations can achieve greater flexibility, efficiency, & reliability by using #Kubernetes☸️ for #LLM workloads💪 To learn how to do this, join Sudhanshu P.’s session on 'Running LLMs Workloads on #Kubernetes' at Cloud Native Gurugram. Register here👇 https://lnkd.in/dYfpsyGJ

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Breaking down a Kubernetes Deployment resource/object 👇 ✅ One of the most used higher-level controllers. ✅ Consists of one or more replicas (Pods). ✅ Gives you the ability to manage all Pods from one place. Self-healing is a big part of higher-level controllers. The goal is to ensure that the current state is the desired state. For example, if you specify 2 replicas in a Manifest, 2 should be running. Deployment objects/resources give you better management over Pods. #kubernetes #devops #platformengineering

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Right-Sizing Pods on Kubernete Efficient resource utilization is key to achieving cost savings and performance in Kubernetes. Right-sizing your pods ensures they have the appropriate CPU and memory requests/limits to handle workloads effectively without overprovisioning. Here's how: 1. Understand Your Workloads : Monitor your application’s resource consumption over time using tools like Prometheus, Grafana, or Kubernetes Metrics Server. Look for patterns in usage during peak and idle times. 2. Set Resource Requests and Limits : - Requests : Specify the minimum CPU/memory a pod needs to run. - Limits : Set the maximum resources a pod can use to prevent noisy neighbors. Though consider throttling and pod evictions. 3. Use Autoscaling Enable Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA) to dynamically adjust resources based on workload demands. 4. Leverage Resource Profiling Tools : Tools like Kubecost , Goldilocks and Kubernetes Resource Recommender provide actionable insights on resource optimization. 5. Test and Iterate : Deploy test environments with adjusted resource configurations, and observe performance. Iteratively refine to strike the right balance between cost and reliability. Right-sizing isn’t a one-time task; it’s an ongoing process as workloads evolve. By doing so, you can optimize performance, reduce costs, and improve cluster efficiency. #Kubernetes #DevOps #CloudComputing #Containers #PodOptimization #SiteReliabilityEngineering #HPA #VPA

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Demystify Containers & Kubernetes deployment on AWS with AWS User Group Delhi NCR leaders Ashish Kumar Dipali Kulshrestha Nitin S. Rajat Arora Tajinder Singh Date- 3 May to 8 June Register at: https://lnkd.in/gXkmCjg5 Topics Covered: - Deep dive into Docker Containers - Understanding Microservice architecture and create your first Microservice - Multi-container deployment - N-tier architecture using Docker - Deploy applications on AWS ECS - Elastic Container Service - Migration Docker app from local to AWS ECS - What is Kubernetes? - Convert and deploy app using K8s inside minikube or kind - Exploring AWS EKS - Serverless offerings of AWS - Deploy N-tier app on EKS - Demystifying Helm

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I wrote this blog entry, "Why Non-Prod to Prod Sequencing is Irrelevant for Kubernetes Patch Versions Upgrade". I noticed that "non-prod then prod patch sequence" fallacy for upgrading patch version is somewhat still living in some Kubernetes practitioners. This raise questions: 1. Does the apps hosted not resilient and easily getting impacted by the platform? Decoupling issue? Fix the app, not the platform. 2. Does not have fully understanding what K8s patch vs minor version introduced? Get the fact straight. 3. Legacy mindset and understanding, brought into container/cloud-native world? Digital transformation also required a mindset shift and the understanding how thing works differently. In this blog, https://lnkd.in/gH3SKHEQ, I am trying to explain why the "non-prod then prod patching sequence" does not really matter for K8s patch-version upgrade. #kubernetes #devops #devsecops #aks #gke #opensource #container

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🆘 In the world of Kubernetes deployments, Terraform and Helm stand out as critical tools that deliver unparalleled efficiency. Combined with the orchestration power of env0, they create a unified platform that blends Kubernetes scalability with Terraform's infrastructure provisioning capabilities and Helm's application deployment prowess. 🕹 Technical Breakdown This diagram highlights how the trio operates within env0 to deliver a streamlined, automated DevOps workflow: ◾ Terraform manages the full lifecycle of the infrastructure, creating an EKS cluster on AWS with precise resource configuration. ◾ Helm handles application deployment with charts, installing a complete monitoring stack (#Prometheus and #Grafana) on the EKS cluster. ◾ env0 serves as the control plane, unifying both tools under a seamless workflow that: - Enables GitOps through version-controlled deployments. - Incorporates robust cost and performance optimization strategies. - Implements layered security and compliance best practices. By leveraging this trio through env0, organizations can streamline their #Kubernetes management processes, enhance their #GitOps practices, and establish a more secure, cost-effective cloud-native environment. For more details: https://lnkd.in/d8ft_vq8

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𝗧𝗼𝗱𝗮𝘆’𝘀 𝘁𝗵𝗲 𝗗𝗮𝘆! Join us at 10:00 AM ET for "Introducing AntStack's AWS SAM Template" with Prashanth HN and Akshatha Laxmi. Learn from the experts how to streamline your serverless projects. 📅 Date: 18th October ⏰ Time: 10:00 AM EDT 🔗 Join Now: https://bit.ly/486MrGR 🔔 Tap 'Notify Me' to get a reminder! #AWSWebinar #ServerlessDevelopment #AWSSAM #ServerlessArchitecture #CloudComputing #AntStack #TechWebinar #OptimizeCode #Serverless #DeveloperCommunity #Webinar #FridayTech #TechNews #TechTrends

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Do you want to run your own Postgresql but don’t know where to start? Fret not! In his latest blog, Anirudh Ramesh writes a practical guide with all the configurations you will need to change in order to get it up and running! Read here: https://lnkd.in/gw67HKdX

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Check our (Arun Chandapillai and Parag Nagwekar) latest blog on DynamoDB Observability and Fine grained access control. https://lnkd.in/gSTcrRh9

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Monitoring Kubernetes Service Topology Changes in Real-Time https://buff.ly/3UFfhsq Horizontally scalable data stores like Elasticsearch, Cassandra, and CockroachDB distribute their data across multiple nodes using techniques like consistent hashing. As nodes are added or removed, the data is reshuffled to ensure that the load is spread evenly across the new set of nodes. When deployed on bare-metal clusters or cloud VMs, database administrators are responsible for adding and removing nodes in a clustered system, planning the changes at times of low load to minimize disruption to production workloads.

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